1,720,985 research outputs found
Defect Evaluation in Pentacene Thin Film Transistors through Photocapacitance and Admittance Spectroscopy Studies
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Light- and bias-induced effects in pentacene-based thin film phototransistors with a photocurable polymer dielectric
Full text linkIn this work, pentacene-based thin film phototransistors were fabricated with a photocurable polymer insulator and their electrical stability was monitored when the devices were exposed to light sources at different wavelengths. The magnitude of the photocurrent induced by illumination was found to be the result of two distinct factors: a direct photocurrent, related to electron–hole pair generation, and a current enhancement caused by a threshold voltage shift. The direction of threshold translation is attributed to the nature of trap states, specifically those located in the pentacene film near the interface with the polymer, and is affected by a measurement-induced effect, so that the photosensitivity can be modulated by a persistent gate bias during illumination. The equations for these two contributions were developed to study the light effects on material structure, the trapping process of electrons at the insulator–semiconductor interface and the photoconductive efficiency in the organic semiconductor
Overcoming Challenges in OLED Technology for Lighting Solutions
No full textIn academic research, OLEDs have exhibited rapid evolution thanks to the development of innovative materials, new device architectures, and optimized fabrication methods, achieving high performance in recent years. The numerous advantages that increasingly distinguish them from traditional light sources, such as a large and customizable emission area, color tunability, flexibility, and transparency, have positioned them as a promising candidate for various applications in the lighting market, including the residential, automotive, industrial, and agricultural sectors. However, despite these promising attributes, the widespread industrial production of OLEDs encounters significant challenges. Key considerations center around efficiency and lifetime. In the present review, after introducing the theoretical basis of OLEDs and summarizing the main performance developments in the industrial field, three crucial aspects enabling OLEDs to establish a competitive advantage in terms of performance and versatility are critically discussed: the quality and stability of the emitted light, with a specific focus on white light and its tunability; the transparency of both electrodes for the development of fully transparent and integrable devices; and the uniformity of emission over a large area
A Model of Electric Field Distribution in Gate Oxide and JFET-Region of 4H-SiC DMOSFETs
No full textFor the first time, a full analytical model of the electric field in the gate oxide of 4H-polytype silicon carbide (4H-SiC) power double-implanted MOSFET devices is shown. It takes into account all the relevant physical and geometrical parameters of the device and avoids the use of any fitting parameters. To validate the results of the full-analytical model, comparisons with numerical simulations are reported for device structures having different values of the drift doping concentration and drift thickness as well as of the junction FET (JFET)-region width. Moreover, because the model equations are in closed form, they can be used to derive an adequate JFET-region geometry by fixing the maximum electric field in the oxide and the maximum blocking voltage for a given drift region
Multiclass Object Classification Using Ultra-Low Resolution Time-of-Flight Sensors
No full textTime-of-Flight (ToF) sensors are generally used in combination with red-blue-green sensors in image processing for adding the 3-D to 2-D scenes. Because of their low lateral resolution and contrast, they are scarcely used in object detection or classification. In this work, we demonstrate that ultra-low resolution (URL) ToF sensors with 8x8 pixels can be successfully used as stand-alone sensors for multiclass object detection even if combined with machine learning (ML) models, which can be implemented in a very compact and low-power custom circuit. Specifically, addressing an STMicroelectronics VL53L8CX 8x8 pixel ToF sensor, the designed ToF+ML system is capable to classify up to 10 classes with an overall mean accuracy of 90.21%. The resulting hardware architecture, prototyped on an AMD Xilinx Artix-7 field programmable gate array (FPGA), achieves an energy per inference consumption of 65.6 nJ and a power consumption of 1.095 mu W at the maximum output data rate of the sensor. These values are lower than the typical energy and power consumption of the sensor, enabling real-time postprocessing of depth images with significantly better performance than the state-of-the-art in the literature
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